Sexual Assault

Fluorescence spectroscopy combined with multilayer perceptron deep learning to identify the authenticity of monofloral honey-Rape honey.

Honey authenticity is critical to honey quality. The development of a quick, easy, and non-destructi...

[Possibilities of the utilization of trauma networks of the German Society for Trauma Surgery using digital solutions].

This paper describes the use of digital solutions to improve the care of trauma patients in Germany....

Enhancing Performance of the National Field Triage Guidelines Using Machine Learning: Development of a Prehospital Triage Model to Predict Severe Trauma.

BACKGROUND: Prehospital trauma triage is essential to get the right patient to the right hospital. H...

A machine learning-based Coagulation Risk Index predicts acute traumatic coagulopathy in bleeding trauma patients.

BACKGROUND: Acute traumatic coagulopathy (ATC) is a well-described phenomenon known to begin shortly...

The potential benefit of artificial intelligence regarding clinical decision-making in the treatment of wrist trauma patients.

PURPOSE: The implementation of artificial intelligence (AI) in health care is gaining popularity. Ma...

Artificial intelligence in paediatric head trauma: enhancing diagnostic accuracy for skull fractures and brain haemorrhages.

Pediatric head trauma is a significant cause of morbidity and mortality, with children, particularly...

Deep Learning-Based Denoising Enables High-Quality, Fully Diagnostic Neuroradiological Trauma CT at 25% Radiation Dose.

RATIONALE AND OBJECTIVES: Traumatic neuroradiological emergencies necessitate rapid and accurate dia...

Automated Association for Osteosynthesis Foundation and Orthopedic Trauma Association classification of pelvic fractures on pelvic radiographs using deep learning.

High-energy impacts, like vehicle crashes or falls, can lead to pelvic ring injuries. Rapid diagnosi...

Diagnostic evaluation of blunt chest trauma by imaging-based application of artificial intelligence.

Artificial intelligence (AI) is becoming increasingly integral in clinical practice, such as during ...

A proposal for cut marks classification using machine learning: Serrated vs. non-serrated, single vs. double-beveled knives.

In tool mark identification, there is still a lack of characteristics and methodologies standardizat...

Machine learning models predict triage levels, massive transfusion protocol activation, and mortality in trauma utilizing patients hemodynamics on admission.

BACKGROUND: The effective management of trauma patients necessitates efficient triaging, timely acti...

The theranostic performance of Chat-GPT against urological trauma.

Integrated Assays of Genome-Wide Association Study, Multi-Omics Co-Localization, and Machine Learning Associated Calcium Signaling Genes with Oilseed Rape Resistance to .

(Ss) is one of the most devastating fungal pathogens, causing huge yield loss in multiple economica...

Prediction of mortality among severely injured trauma patients A comparison between TRISS and machine learning-based predictive models.

BACKGROUND: Given the huge impact of trauma on hospital systems around the world, several attempts h...

Knowledge, attitudes and practices of using Indocyanine Green (ICG) fluorescence in emergency surgery: an international web-based survey in the ARtificial Intelligence in Emergency and trauma Surgery (ARIES)-WSES project.

Fluorescence imaging is a real-time intraoperative navigation modality to enhance surgical vision an...

Machine Learning Differentiates Extracorporeal Membrane Oxygenation Mortality Risk Profiles Among Trauma Patients.

BACKGROUND: Extracorporeal membrane oxygenation (ECMO) is resource intensive with high mortality. Id...

Value of vendor-agnostic deep learning image denoising in brain computed tomography: A multi-scanner study.

To evaluate the effect of a vendor-agnostic deep learning denoising (DLD) algorithm on diagnostic im...

Assessment of artificial intelligence applications in responding to dental trauma.

BACKGROUND: This study assessed the consistency and accuracy of responses provided by two artificial...

Predicting blood transfusion following traumatic injury using machine learning models: A systematic review and narrative synthesis.

BACKGROUND: Hemorrhage is a leading cause of preventable death in trauma. Accurately predicting a pa...

Using machine learning to increase access to and engagement with trauma-focused interventions for posttraumatic stress disorder.

BACKGROUND: Post-traumatic stress disorder (PTSD) poses a global public health challenge. Evidence-b...

The application of deep learning in abdominal trauma diagnosis by CT imaging.

BACKGROUND: Abdominal computed tomography (CT) scan is a crucial imaging modality for creating cross...